Custom dimensions

Custom dimensions are additional ways to group and analyze your data beyond standard metrics. They're like creating your own categories that matter specifically to your product. For example, if you run a content website, you might create custom dimensions for content categories, article length, or author names.

When you set up custom dimensions, you're essentially adding new labels to your analytics data. These labels can be applied to users (like membership level), sessions (like logged-in status), or individual events (like article topic). This extra context helps you analyze data in ways that standard analytics categories don't cover.

A practical example would be tracking a "Reading Time" dimension with values like "Quick Read (2-5 mins)," "Medium (5-10 mins)," or "Long Form (10+ mins)" for your blog posts. This would let you analyze how article length affects metrics like completion rates, social shares, and return visits. For instance, you might discover that while long-form content gets more shares, quick reads lead to higher reader retention and more frequent return visits.